Triple
T13483861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakki Marwat District |
E318441
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Lakki Marwat city |
E999576
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lakki Marwat city | Statement: [Lakki Marwat District, hasSettlement, Lakki Marwat city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lakki Marwat city Context triple: [Lakki Marwat District, hasSettlement, Lakki Marwat city]
-
A.
Amarkot
Amarkot is an alternative name for Umarkot, a historic town and district in the Sindh province of Pakistan known for its cultural and Mughal-era significance.
-
B.
Lakki Marwat
chosen
Lakki Marwat is a town and district headquarters in Khyber Pakhtunkhwa, Pakistan, known for its predominantly Pashtun population and agricultural surroundings.
-
C.
Shikarpur
Shikarpur is a historic city in the Sindh province of Pakistan, known for its old trading heritage and distinctive cultural and architectural traditions.
-
D.
Jauharabad
Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
-
E.
Haroonabad
Haroonabad is a town in Pakistan known for its agricultural surroundings and role as a local commercial center.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf3868ec8190a6a1803018d4f2d8 |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7463715dc8190a70a17b3ea661006 |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:42 p.m.